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of 4
pro vyhledávání: '"Katherine A. Macmillan"'
Autor:
Alessio J. Sprockel, Mohd A. Khan, Mariska de Ruiter, Meyer T. Alting, Katherine A. Macmillan, Martin F. Haase
Publikováno v:
Colloids and Surfaces A: Physicochemical and Engineering Aspects. 666:131306
Autor:
Paul S. Clegg, Katherine A Macmillan
Publikováno v:
The journal of physical chemistry letters. 12(22)
While studies carried out in a Langmuir trough have rigorously demonstrated that, at high surface pressure, ellipsoidal particles do flip and spherocylinders (rods) can flip, much less is known about the practical situation on the surface of a drople
Autor:
Alexander Morozov, John R. Royer, Katherine A Macmillan, Yogesh M. Joshi, Paul S. Clegg, Michel Cloitre
Publikováno v:
Langmuir
Langmuir, American Chemical Society, 2019, 35 (33), pp.10927-10936. ⟨10.1021/acs.langmuir.9b00636⟩
MacMillan, K A, Royer, J, Morozov, A, Joshi, Y M, Cloitre, M & Clegg, P 2019, ' Rheological Behavior and in Situ Confocal Imaging of Bijels Made by Mixing ', Langmuir . https://doi.org/10.1021/acs.langmuir.9b00636
Langmuir, American Chemical Society, 2019, 35 (33), pp.10927-10936. ⟨10.1021/acs.langmuir.9b00636⟩
MacMillan, K A, Royer, J, Morozov, A, Joshi, Y M, Cloitre, M & Clegg, P 2019, ' Rheological Behavior and in Situ Confocal Imaging of Bijels Made by Mixing ', Langmuir . https://doi.org/10.1021/acs.langmuir.9b00636
Bijels (bicontinuous interfacially jammed emulsion gels) have the potential to be useful in many different applications due to their internal connectivity and the possibility of efficient mass transport through the channels. Recently, new methods of
Publikováno v:
Gould, E, Macmillan, K A & Clegg, P 2020, ' Autonomous analysis to identify bijels from two-dimensional images ', Soft Matter . https://doi.org/10.1039/C9SM02187F
Soft Matter, 16, 2565. The Royal Society of Chemistry
Soft Matter, 16, 2565. The Royal Society of Chemistry
Bicontinuous interfacially jammed emulsion gels (bijels) are novel composite materials that can be challenging to manufacture. As a step towards automating production, we have developed a machine learning tool to classify fabrication attempts. We use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b6a9c0436d84912791f0431a9c1a073
https://www.pure.ed.ac.uk/ws/files/134990565/AcceptedManuscript.pdf
https://www.pure.ed.ac.uk/ws/files/134990565/AcceptedManuscript.pdf